What do computer scientists do?

In this paper, we provide a statistical analysis of data from the California Department of Education to determine whether students of different ethnic and gender backgrounds are equally represented in high school computer science classes in California. Contrary to public perception, we found that every ethnic demographic was accurately represented in the classroom. The percentage of students of each demographic matched in the classroom the percentage of students in each demographic for the state. We found that this representation does not depend on gender. The ethnic distribution of male students in computer science matches the ethnic distribution of the state of California. Similarly, the ethnic distribution of female students in computer science matches the ethnic distribution of the state of California. We found that, despite inclusion efforts, female students are still a minority in these classes. Only 15% of schools with computer science programs have enrollment of at least 50% female. Related research suggests that the most effective way to include female students is to integrate STEM programs into the school curriculum at an early age before girls start to associate with gender stereotypes.

This research shows an audience of fellow computer science teachers that there is benefit in testing college student's scientific reasoning skills and that the students increase their logical thinking skills in computer science classes when they are presented with real world problems, engaged in group activities, and given hands-on experiments.Students' scientific reasoning skills from several different computer science courses are analyzed and tested before and after taking the computer science course to measure their improvement in logical thinking. The higher order thinking skills test results are compared, and the overall class and individual student improvement between the classes that use different teaching strategies are analyzed. Also, the test results are compared with students' ability to perform adequately in a computer science course. This information is valuable to advisors when placing students in computer science courses.In the assessments of students' entering knowledge and evaluations of students' thinking improvement, the students' individual higher order thinking skills as well as their overall level of cognitive development are analyzed. Through the analysis of their individual skills and level of thinking, one can expand conclusions about the students' and teacher's performance over time.

In the context of higher education strongly transforming itself under the impact of technology, Artificial Intelligence (AI) has become an important support tool in the learning process, especially for Computer Science (CS) students. Integrating a structured literature review and conceptual analysis, this paper evaluates the role of AI as a self-learning assistant, focusing on outstanding benefits such as personalized learning, source code debugging, and explaining complex algorithms, as well as challenges related to academic integrity, ethics, and independent thinking skills of students. Through analysis, the paper proposes a comprehensive recommendation framework, including: (1) an in-depth analysis of the five most effective AI tools; (2) smart strategies for AI-use through Prompt Engineering; (3) new pedagogical approaches for instructors; and (4) support policies from institutions. The results indicate that although AI cannot substitute human instructors completely, it can act as a powerful lever to enhance self-learning capabilities. When applied appropriately, it contributes to elevating the quality of Computer Science education in universities. Keywords: AI-assisted learning, Artificial Intelligence, Computer Science students, higher education, self-learning assistant.

Previous research in STEM education demonstrates that students are engaged in a process of identity trying to integrate their educational experiences with their perception of who they are, and who they wish to become. It appears increasingly apparent from this body of research that students are not well supported in this process by the education they currently receive. The goal of this paper is to analyse a specific aspect of the student experience, participation, in order to gain a better understanding of how computer science (CS) and information technology (IT) students engage with CS prior to and during their studies. Drawing on student interview data we describe and discuss students' qualitatively different ways of experiencing participation in CS and IT. The notion of participation applied here is inspired by Wenger's notion of participation in his social theory of learning. A phenomenographic analysis identifies a spectrum of qualitatively distinct ways in which the students experience participation in CS and IT, ranging from using, to participation as continuous development, and creating new knowledge.

Despite great effort in research and teaching as well as in raising women’s quotas in the public sector and in enterprises, a gender gap in computer science can still be observed. The reasons are manifold, including the lack of interest of girls because of existing stereotypes of male nerds, misconceptions in the field of computer science, and concrete differences in students’ self-concept and performance. Girls do not choose schools or studies in the field of computer science because working on computers or coding is unattractive to them. Research shows poorer performance, missing interest, and lower self-concept for girls in secondary computing education as well as a high dropout rate of female students in computer science courses at the bachelor’s level. Software development exams contribute to those high dropout rates, and women often choose a different subject or even stop their university education altogether. This leads to fewer female employees in the field of computer science, and this situation calls for special measures at several levels. The current paper provides an overview of the initiatives of our university that aim to address several aspects of the gender gap. The programs offered aim to (1) increase interest in computer science and recruit (highly) gifted girls for our talent programs, (2) recruit and support female bachelor’s and master’s students in computer science, and (3) redesign programming courses and teaching materials to reduce the gender gap in performance and support, especially for female students. This study also describes a cyber tutoring program in which highly gifted girls between 13 and 16 years collaborate with and are supervised by female role models in higher positions in STEM. The evaluation results gained in the first year of this case study are promising and suggest that the extension and further development of the program would be advantageous.

Most studies of gender and computer science have been conducted (out of necessity) in gender-imbalanced environments. The findings often point to significant gender differences, leading the researchers to recommend strategies to meet these differences. One such recommendation is to adopt a female-friendly, contextual approach to curriculum development.1 In contrast, based on our recent and ongoing studies of undergraduate computer science (CS) students at Carnegie Mellon University, we hypothesize that in a more balanced environment, gender differences tend to dissolve. That is, the spectrum of interests, motivation, and personality types of men and of women becomes more alike than different. This leads us to be considerably more pragmatic in our recommendations for effective and positive change. Indeed, we believe that recommendations for curricular changes based on presumed gender differences can be misguided and may help reinforce, even perpetuate, stereotypes. Here, we describe some of the changes in the culture of computing as our undergraduate CS environment has become more balanced in three critical domains: gender, the mix of students and breadth of their interests, and the professional experiences afforded all students. Brief Background for the Evolving Culture In 1995, just 7percent (7 out of 96) of the entering freshmen CS majors at Carnegie Mellon were women. Since 1999, the percentage has increased nearly fivefold (on average, 45 out of 132), challenging trends across the country.2 Two major factors have contributed to the dramatic increase of women in CS at Carnegie Mellon: an outreach program for high school CS teachers that combined technical training with discussions of gender-gap issues and a broadened admissions policy (emphasizing diverse interests—along with high [End Page 110] achievement in mathematics and science—and de-emphasizing prior programming experience). To meet the needs of students with varying backgrounds, multiple entry routes were built into the first-year programming sequence.3 The subsequent creation of the proactive student organization Women@SCS has been catalytic in building an environment in which the new student body can flourish.4 Women@SCS explicitly provides crucial educational and professional experiences generally taken for granted by the majority in the community but typically unavailable for the minority participants.5 Many of these experiences are casual and often happen in social settings. For example, in an undergraduate CS program, male students often have the opportunity to discuss homework with roommates, with friends late at night, or over meals. Course and job information and recommendations are passed down from upperclassmen, from fraternity files, or from friends. Women students, being in the minority, do not have access to—in fact are often excluded from—these implicit and important advantages. As one proceeds into the professional world, similar phenomena occur. These key actions, and implications for other venues, are discussed further at the end of this paper. Our recent study, based on a set of interviews with seniors in the class of 2002, may be viewed to a limited degree as a follow-up to the intensive longitudinal studies of CS students at Carnegie Mellon carried out by Jane Margolis and Allan Fisher between 1995 and 1999.6 Their studies, funded by the Sloan Foundation and discussed in Unlocking the Clubhouse, were undertaken to help understand differences in male and female students' engagement (attachment, persistence, and detachment) with computer science, with a special focus on the gender imbalance in the field.7 A major goal was to devise and effect changes in recruitment, curriculum, pedagogy, and culture to encourage the broadest possible participation in the computing enterprise. Unlocking the Clubhouse paints a bleak picture for women in the undergraduate computer science program in the 1990s, one that still resonates with many CS programs across the nation. Margolis and Fisher note that for the most part, "women who were enthusiastic about computing find their confidence and interest extinguished in the college years."8 Consequently, many of the (few) women students who entered the...

Different points of view on the nature and content of the assertiveness are followed in this paper. The main purpose is to study the assertive profile of Bulgarian students in computer science and computer engineering by analyzing the components of assertiveness. Research was performed using testing methods. It was found that the level of expressivity of this personal quality among subjects were above-average level.

This case study introduces the STARS (Supporting Talented African American Undergraduates for Retention and Success) project, designed to foster the retention and success of academically talented African American computer science students from low-income backgrounds at Historically Black Colleges and Universities (HBCUs) in the U.S. The STARS program employs a holistic approach, integrating four primary pillars of support: academic, social, career, and financial. Specific support provided includes near-peer mentoring, technical skill development seminars, undergraduate research, and high school outreach activities. To explore the program’s effectiveness and areas of improvement, a mixed-method evaluation study was conducted, collecting data through surveys, observations, individual interviews, and focus group interviews. The findings revealed that the STARS program contributed to high levels of retention among its scholars, and the mentoring program provided valuable networking opportunities. The study suggests that the program’s comprehensive approach, tailored to scholars’ needs, and combined with a culturally affirming learning environment, facilitates the retention and success of talented African American students in computer science.

Nowadays, Computer Science (CS) students must cope with continuous challenges related to programming skill acquisition. In some occasions, they have to deal with the internals of memory management (pointers, pointer arithmetic, and heap management) facing a vision of programming from the low abstraction level offered by C. Even using C++ and references, not all scenarios where objects or collections of objects need to be managed can be covered. Based on the difficulties identified when dealing with such low‐level abstractions, the C‐Sim application, aimed at learning these concepts in an easy way, has been developed. To support the tool, the C programming language was selected. It allows showing concepts, remaining as close as possible both to the hardware and the operating system. To validate C‐Sim, pre and posttests were filled in by a group of 60 first‐year CS students, who employed the tool to learn about memory management. Grades of students using C‐Sim were also obtained and compared with those that did not use the tool the former academic year. As main outcomes, 82.26% of students indicated that they had improved programming and memory management knowledge, and 83.64% pointed out that the use of this type of tools improves the understanding and quality of the practice lessons. Furthermore, the marks of students have significantly increased. Finally, C‐Sim was designed from the ground up as a learning aid and can be useful for lecturers, who can complement their lessons using interactive demonstrations. Students can also employ it to experiment and learn autonomously.

This study investigates gender differences in attitudes toward mathematics among first-year Computer Science (CS) students, focusing on three key dimensions: self-confidence, enjoyment, and value. Understanding students’ affective orientations toward mathematics is crucial, as these attitudes can influence their engagement, persistence, and performance in mathematics-related courses. The study aims to determine whether male and female students differ significantly in their levels of self-confidence, the value they place on mathematics, and the degree of enjoyment they derive from the subject. A total of 114 first-year CS students participated in the study and completed a structured questionnaire designed to measure the three attitude dimensions. The instrument’s reliability was confirmed through internal consistency analysis, while the Mann–Whitney U test was employed to assess gender differences in the responses. The findings revealed no statistically significant gender differences in self-confidence and enjoyment, suggesting that male and female students hold similar levels of belief in their mathematical abilities and experience comparable levels of positive affect toward the subject. However, the analysis identified a small but significant difference in perceived value, with female students reporting a stronger recognition of mathematics as valuable in their academic and professional pursuits than their male counterparts. These results suggest that while self-confidence and enjoyment in mathematics appear unaffected by gender among CS students, female students may place greater importance on the role of mathematics in their studies and future careers. The study contributes to the growing body of literature on gender and mathematics attitudes, highlighting the need for educators to acknowledge and leverage these perceptions to foster equitable and supportive learning environments.

There has been an increasing tendency and an interest to make computer science (CS) a core subject in the K-12 curriculum, however in many countries there is a CS teacher shortage in high schools. In order to define the possible reasons for CS teacher shortage, we investigated the factors that influence CS students’ career choices and their preferences about teaching. We also studied the requirements students view as important for their career. Semi-structured interviews were conducted with 18 CS bachelor and master students from four different universities in the Netherlands. The results show that the most important factors influencing the career choice of CS students are organization related expectations such as the characteristics of the organization (scale, reputation etc.), the field of expertise and salary expectations. Regarding CS students career plans about becoming a teacher, a large part (almost 75%) of the students stated that they definitely do not think of teaching or teaching is not a priority career goal. The most cited demotivating factors for following a teaching career are the nature of the teaching job and low salaries. Perceived required skills for good CS teachers are frequently defined as pedagogical skills and social skills.

This study aims to identify the effect of the teaching method using educational software based on artificial intelligence in the academic achievement of 10 th -grade students in computer science in Jordan and their attitudes towards it. To achieve the goal of this study, a computerized software was designed to be applied to a purposefully selected sample consisting of (50) 10 th -grade students at The University of Jordan School. The study sample was randomly distributed into two groups: an experimental sample taught using the educational software, and a control sample taught in the traditional method, where the researcher prepared an achievement test to measure the academic achievement of the 10 th -grade students in the Computer Science Subject, where the validity and reliability of the test has been validated, and the test-retest reliability coefficient was (0.86). A questionnaire was prepared for the attitudes, where their validity and reliability were validated. The reliability factor of the questionnaire based on Cronbach’s alpha equation was (0.01). To analyze the results, an analysis of covariance (ANCOVA) was used, where the results of the study showed that there are statistically significant differences in favor of the experimental group taught using educational software based on artificial intelligence in learning computer science subject. The results also showed that there are medium positive attitudes of the experimental group towards educational software. The study recommended designing and developing computerized software in the field of teaching computer science subject s and training and encouraging teachers to use artificial intelligence-based learning in the field of basic education. Keywords: artificial intelligence software, academic achievement, student attitudes, University of Jordan School DOI: 10.7176/JEP/11-7-10 Publication date: March 31 st 2020

Universities of Applied Sciences in Austria offer study courses especially designed and optimized for today needs of companies and students. During the last 20 years, several approaches have been worked out. Feedback of companies employing graduates and feedback of students are among the main driving factors in the process of optimizing these study programs. An important need of adaption of study programs arises from the preferences of students [1]. Today almost all students of computer science start to work in their field while still studying. In many cases, this comes from the fact that companies are intensively trying to attract students, as the labor market in the IT field increasingly demands personnel. This in turn leads to many dropouts of students who are not going to finish their studies. One approach to overcome this problem is to integrate the education experienced while working in companies with the education of students in computer science. At the University of Applied Sciences Technikum Wien, such a program started on the bachelor level in computer science [2]. In the present paper, the authors describe a program on the master’s level in software engineering, which is scheduled to be introduced in fall 2021.

There were more than 60 participants and 46 talks

This Research to Practice Full Paper discusses an approach to motivating graduate computer science and electrical engineering students in the study of quantum computing. The U.S. Congress and other governmental and industrial organizations have recognized that teaching Quantum Computing in university-level Computer Science and Electrical Engineering programs is strategically important for workforce development along with technology development. Success in this endeavor requires generating genuine interest in the topic and motivating potential students. Quantum Computing requires an understanding of relatively difficult related subjects including physics, math and computer science. Many computer science and electrical engineering students shy away from quantum computing because of its complexity. This paper discusses our success with generating interest in quantum computing among graduate students and motivating them through exploring, in related courses, some aspects of quantum computing that have the potential to generate discontinuities. The approach is also examined in terms of the Scientific Learning Cycle as discussed by Wankat & Oreovicz. Opportunities and challenges of adding Quantum Computing to Computer Science and Electrical Engineering programs were studied through a student small group project in a cybersecurity course. The work built on extensive research into the effectiveness of small group projects and the role of “play” in learning. Our small group project on quantum computing was introduced three years ago into a cybersecurity course which is required for all students in our university's Masters in Computer Science and Masters in Electrical Engineering programs. The basic goals of the project are to teach students some basics of quantum computing by allowing them to “play with it” and to alert students to the fact that quantum computing is a rapidly developing new field that they need to follow during at least the next decade. The small group project helped students to explore the potential of quantum computing to substantially undermine current Public Key Cryptography and, at the same time provide a new approach to encryption that is even more secure than Public Key Cryptography. A qualitative analysis of discussions and assigned tasks suggests that this strategy succeeded in generating significant interest in quantum computing among students. They became motivated and immersed in a difficult subject despite the requirement for investment of significant time and effort to understand a complex combination of physics, math and computer science.